Continuous Optimization

Unique sparse decomposition of low rank matrices NeurIPS 2021 Unitary Branching Programs: Learnability and Lower Bounds ICML 2021 Value-at-Risk Optimization with Gaussian Processes ICML 2021 Variance Reduction via Primal-Dual Accelerated Dual Averaging for Nonsmooth Convex Finite-Sums ICML 2021 Vector Transport Free Riemannian LBFGS for Optimization on Symmetric Positive Definite Matrix Manifolds ACML 2021 Vocabulary Learning via Optimal Transport for Neural Machine Translation ACL 2021 Wasserstein barycenters can be computed in polynomial time in fixed dimension JMLR 2021 Why Do Attributes Propagate in Graph Convolutional Neural Networks? AAAI 2021 XOR-CD: Linearly Convergent Constrained Structure Generation ICML 2021 XOR-SGD: provable convex stochastic optimization for decision-making under uncertainty UAI 2021 A Catalyst Framework for Minimax Optimization NeurIPS 2020 Accelerated Factored Gradient Descent for Low-Rank Matrix Factorization AISTATS 2020 Accelerated Primal-Dual Algorithms for Distributed Smooth Convex Optimization over Networks AISTATS 2020 Accelerated Stochastic Gradient-free and Projection-free Methods ICML 2020 Acceleration through spectral density estimation ICML 2020 Acceleration with a Ball Optimization Oracle NeurIPS 2020 A Certifiably Globally Optimal Solution to Generalized Essential Matrix Estimation CVPR 2020 A Class of Parallel Doubly Stochastic Algorithms for Large-Scale Learning JMLR 2020 A Continuous-Time Mirror Descent Approach to Sparse Phase Retrieval NeurIPS 2020 A Continuous-time Perspective for Modeling Acceleration in Riemannian Optimization AISTATS 2020 A convex optimization formulation for multivariate regression NeurIPS 2020 Acoustic Signal Enhancement Using Relative Harmonic Coefficients: Spherical Harmonics Domain Approach Interspeech 2020 Adaptive multi-fidelity optimization with fast learning rates AISTATS 2020 Adaptive Online Estimation of Piecewise Polynomial Trends NeurIPS 2020 Adaptive Reduced Rank Regression NeurIPS 2020